Data readiness
Nobody can say what is ready today
You don't find out a product isn't ready until a channel rejects the feed, or a market launch goes out with no copy in the locale.
The same product stops being described four different ways across channels. Localisation cost per SKU, per market becomes a number you can put in front of the board, not a moving target.
How it works
Intake, enrich, validate, score
Speedtrain enriches straight from messy supplier feeds, and completeness is visible before anything is published.
- 1
Intake
Units and taxonomy are normalised on arrival, each product gets a stable identity, and gaps are recorded rather than invented.
- 2
Enrich
Speedtrain applies per-attribute rules that are versioned and testable, with roughly 80 percent auto-approved and the rest queued for review. Every value keeps a record of where it came from and how certain it is, so guesses are countable.
- 3
Validate
The regulated attribute set for each market and category comes with validity dates and sources, and a new rule flags who fails it before a channel blocks them.
- 4
Score and publish
Completeness is scored per market and dialect continuously. Enterspeed Core projects one representation into each channel dialect, and each channel keeps a record of what went live when and what was rejected.
The gap report runs on your own catalogue before any integration work is scoped, showing completeness and gaps per market and per channel with no project prerequisite. Your PIM authors, the ERP holds the source data, and supplier documents stay with your existing intake process.
Where teams start
Start on the catalogue you have
The gap report is the first deliverable, not a prerequisite you have to prepare for.
You need the gaps visible before you can clean anything. The report runs on your catalogue as it is, showing what is missing per market and per channel, and none of that waits on integration work.
One category is enough. A supplier file and an extract from the PIM, and the report lands in days with nothing for your team to implement.
- How many products are publish-ready in each market today
- Which regulatory attributes are missing, per market and category
- What content and localisation cost per SKU per market
A PIM with AI enrichment sees PIM data. This reads PIM, ERP, supplier specifications and market context, checks the output before anything publishes, and does not care which model runs the generation. Your approval step still decides what goes live, and your team spends its time on what needs judgement.
